| 滚动轴承故障信号的数学形态学提取方法 | |
| 郝如江 ; 卢文秀 ; 褚福磊 ; HAO Ru-jiang ; LU Wen-xiu ; CHU Fu-lei | |
| 2010-05-13 ; 2010-05-13 | |
| 关键词 | 滚动轴承 形态非抽样小波变换 故障诊断 包络解调 roller bearing morphological undecimated wavelet transform faults diagnosis enveloping demodulation TH133.33 |
| 其他题名 | Mathematical Morphology Extracting Method on Roller Bearing Fault Signals |
| 中文摘要 | 基于非线性数学形态变换的概念设计了形态非抽样小波变换算法,通过构造信号分解算子和结构元素,经过多尺度形态小波分解既能够平滑噪声又提取了信号中的故障特征成分。分别对模拟信号和实验数据进行分析处理,结果均表明该方法对信号冲击特征的提取是有效的。最后通过与包络解调分析方法的对比,说明了形态非抽样小波变换对滚动轴承故障特征的提取效果更明显。由于形态非抽样小波变换算法只涉及加减和取极大、极小运算,运算简单,执行高效,非常适于滚动轴承故障的在线监测和诊断。; Based on mathematical morphology theory, the morphological undecimated wavelet transform (MUWT algorithm was presented according to the shape feature of the signals. The multi-scale MUWT operation can not only smooth the background noises but also extract the characteristic components by constructing the signal decomposition operator and the structuring elements. This method was used to analyze the simulated data and measured signals from the bearing tes rig. The results reveal that it is effective to the impulse characteristics extraction. Comparied with the norma enveloping demodulation method, the MUWT operation i more simple and effective for defect diagnosis in the rolle bearing. The MUWT algorithm includes addition, subtraction maximum and minimum operations, and does not involve multiplication and division, the signal information is not lost in the decomposition procedure. It is suitable for the on-line fault monitoring and diagnosis of roller bearing. |
| 语种 | 中文 ; 中文 |
| 内容类型 | 期刊论文 |
| 源URL | [http://hdl.handle.net/123456789/31135]  |
| 专题 | 清华大学 |
| 推荐引用方式 GB/T 7714 | 郝如江,卢文秀,褚福磊,等. 滚动轴承故障信号的数学形态学提取方法[J],2010, 2010. |
| APA | 郝如江,卢文秀,褚福磊,HAO Ru-jiang,LU Wen-xiu,&CHU Fu-lei.(2010).滚动轴承故障信号的数学形态学提取方法.. |
| MLA | 郝如江,et al."滚动轴承故障信号的数学形态学提取方法".(2010). |
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